Technical Field
Embodiments disclosed herein relate to associating meaningful expressions with abbreviated names that reference data stores.
Brief Description of Related Art
Many organizations maintain large stores of data related to their business or endeavor. There is a growing trend towards analyzing these data stores to improve research and business practices. For example, businesses analyze customer churn rates in order to improve customer retention. Data scientists employed to gather and analyze relevant data are limited based on their ability to find appropriate data to process. However the ability to find appropriate data can be impeded by the use of abbreviated names to reference the data stores and data store entities. Additionally, search engines can have difficulty processing abbreviated names when responding to a search query. Furthermore, data stores are often poorly documented, or not documented at all, without providing sufficient clues to clarify the meaning of abbreviated names. One solution is to task subject matter experts with manually mapping the abbreviated names to meaningful expressions or categories. However, this solution is difficult to perform on a large scale, requiring significant human effort and time. Other solutions analyze actual data in data stores. However accessing sensitive content has security limitations.